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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About
About
Some fun things made using P5.js
And you may ask yourself, “Well… how did I get here?”
Posts
Imperial MSc FAQ
Published:
Heading
Subheading
A number of prospective MSc students have reached out to me in the past with questions about the MSc in AI and ML at Imperial, I’ve compiled some of my answers here.
publications
Nonlocal Thresholds for Improving the Spatial Resolution of Pixel Detectors
Published in Journal of Instrumentation, 2019
Investigating the potential use of charge sharing between neighboring pixels in HEP sensors to increase resolution and radiation hardness.
Nachman, B. & Spies, A.F. (2019). Nonlocal Thresholds for Improving the Spatial Resolution of Pixel Detectors. Journal of Instrumentation. [BIB] [PDF]
Sparse Relational Reasoning with Object-Centric Representations
Published in ICML Dynn Workshop (Spotlight), 2022
Assessing the extent to which sparsity and structured (Obect-Centric) representations are beneficial for neural relational reasoning.
Spies, A.F., Russo, A., Shanahan, M. (2022). Sparse Relational Reasoning with Object-Centric Representations. ICML 2022 DyNN Workshop. [BIB] [PDF]
A Configurable Library for Generating and Manipulating Maze Datasets
Published in arXiv preprint, 2023
A dataset to generate simple Maze-like environments for use with Transformers.
Ivanitskiy, M.I., Shah, R., Spies, A.F. et al. A Configurable Library for Generating and Manipulating Maze Datasets. arXiv, 10.48550/arXiv.2309.10498 (2023). [BIB] [PDF]
Structured World Representations in Maze-Solving Transformers
Published in NeurIPS 2023 UniReps Workshop, 2023
Transformers trained to solve mazes form linear representations of maze structure, and acquire interpretable attention heads which facilitate path-following.
Ivanitskiy, M.I.*, Spies, A.F.*, Räuker, T.* et al. Structured World Representations in Maze-Solving Transformers. NeurIPS 2023 UniReps Workshop. [BIB] [PDF]
talks
teaching
Introductory Python Course
Extracurricular course, University of Manchester, CS Department, 2018
Materials
Available online at this link
Deep Learning
Master's Course, Imperial College London, Department of Computing, 2020
Designed Coursework on VAEs and GANs alongside Harry Coppock. Prepared an tutorial on Attention mechanisms in Deep Learning. Taught students in Lab Sessions, answered questions and oversaw coursework marking. Spearheaded efforts to use Paperspace platform to allow students to train models with greater compute.
Computer Architecture
Undergraduate Course, Imperial College London, Department of Computing, 2021
Taught in lab sessions as a teaching assistant, and marked course work.
Data Structures and Algorithms
Undergraduate Course, Imperial College London, Department of Computing, 2021
Taught Imperial business students in lectures and tutorial sessions. Additionally, co-created and ran extended weekly workshop alongside Hadeel Al-Negheimish.
Maths for Machine Learning
Master's Course, Imperial College London, Department of Computing, 2021
Taught in lab sessions as a teaching assistant.
Deep Learning
Master's Course, Imperial College London, Department of Computing, 2021
Acting as a Course Support Leader, developed an autograding framework for the courseworks, combining existing departmental tools with Otter Grader to automatically mark students’ Jupyter Notebook submissions - including unit tests for various Deep Learning models. Additionally, aided with other material creation and organization, and answered many student queries.